The present invention in general relates to an adaptive array communication system that removes an unnecessary signal by using an adaptive array technique. More particularly, this invention relates to an adaptive array communication system and a receiver capable of realizing an improvement in demodulation characteristic by efficiently removing interference in a fading environment of a land mobile communication or the like.
A conventional receiver will be described below. For example, a conventional receiver using an adaptive array antenna technique which is one of techniques for improving bit error rate performance in a receiver will be described below.
As a technique related to a conventional receiver, for example, xe2x80x9cAdaptive Array for Mobile Radioxe2x80x9d (Ohgane, Ogawa, November, 1998 to March, 1999) described in Journal of The Institute of Electronics, Information and Communication Engineers is known. The adaptive algorithm itself is described in a reference xe2x80x9cIntroduction to Adaptive Filtersxe2x80x9d (S. Haykin, translated by Tsuyoshi TAKEBE, Gendai Kogaku sha, Third Edition, on Mar. 10, 1994).
For example, in land mobile communication such as a portable telephone system, a base station is installed corresponding to each one of a plurality of areas. These areas are generally called as cells. Mobile stations existing in a cell communicate with the base station of that cell. In this case, for a mobile station in the cell, a radio wave from the base station in the same cell is a desired wave. Similarly, for the base station in the cell, a radio wave from the mobile station in the same cell is a desired wave. However, a mobile station existing near a boundary of another cell receives interference from a mobile station existing in another cell using the same frequency and a base station of another cell which communicates with the mobile station. Since the transmission power of a base station is generally higher than the transmission power of a mobile station, the base stations receive the interference the most.
In such a case, in an adaptive array communication system, a plurality of antennas (array) are used, and the directivity of the array is adaptively controlled, so that the process of removing an interference wave except for a desired wave and the process of combining a plurality of desired waves reflected from buildings or the like and having different arrival times are performed. More specifically, a directivity (beam) is turned in a desired wave direction, and a point where the beam is 0 (null) is turned in an interference direction to remove an interference wave. A plurality of beams are turned toward a plurality of desired waves to equalize delays and to combine desired waves, so that a preferable characteristic is realized.
FIG. 15 is a diagram showing the configuration of a conventional receiver. In FIG. 15, as one example of the conventional receiver, an adaptive array communication system using mean square error (MSE) criteria is shown. In this receiver, received signals from a plurality of antennas (branches) are weighted by coefficients (complex weights) which are different from each other for the respective branches, and a signal is combined. At this time, in the adaptive array communication system, on the basis of the received signals from the branches and the combined signal (array output), a such optimum complex weight that a desired wave is increased and an unnecessary wave is decreased in the array output is determined.
The details of the operation of the conventional receiver will be described below. In the adaptive array communication system of N branches (N: a natural number of 2 or more) using the MSE criteria shown in FIG. 15, an optimum complex weight wj is determined by using a known reference signal di included in the received signals. First, inputs Xj,i (j is a branch number: j=1 to N and i is an integer representing a symbol timing) of branches are multiplied by the complex weights wj output from an adaptive control unit 181 in a multiplier. Signals multiplied by the complex weights wj are input into an adder 182 and added (combined) to each other to calculate an array output yi. More specifically,                               y          i                =                              ∑                          j              =              1                        N                    ⁢                                    w              j                        ⁢                          x                              j                ,                i                                                                        (        1        )            
is satisfied.
Thereafter, the array output yi is input into a demodulation unit (not shown) and input into an adder 183 to be compared with the known reference signal di. As a result, an error signal xcex5i is output from the adder 183. More specifically,
xcex5i=dixe2x88x92Yixe2x80x83xe2x80x83(2)
is satisfied.
The error signal xcex5i output from the adder 183 is, thereafter, input into the adaptive control unit 181. In the adaptive control unit 181, by using the error signal xcex5i, the complex weight wj is controlled on the basis of an adaptive algorithm. For example, when an LMS (Least Mean Square) as the adaptive algorithm, the complex weight is changed (controlled) by the following equation:
wj,i+1=wj,i+2xcexcxj,1*xcex5ixe2x80x83xe2x80x83(3)
Note that wj,i represents the complex weight wj including a symbol timing. In the following, * represents a complex conjugate.
According to Equations (1) , (2), and (3), the complex weight wj is controlled to such an optimum value that a desired wave is maximum and an interference wave is minimum in the array output yi. In this manner, since the signal controlled to the optimum value is demodulated, the adaptive array communication system can improve bit error rate performance in the array output yi. Therefore, for example, when the adaptive array communication system shown in FIG. 15 is applied to a system using convolutional coding/viterbi decoding as shown in FIG. 16, the bit error rate performance in the array output yi is improved. For this reason, bit error rate performance in a decoded output of a viterbi decoder can be improved.
In addition, as a conventional receiver different from the above receiver, for example, an adaptive array communication system using a decision feedback loop is known. FIG. 17 is a diagram showing the configuration of a conventional receiver using a decision feedback loop. In this case, the complex weight wj is updated by an adaptive algorithm using data except for the known reference signal di. The same reference numerals as in the configuration in FIG. 15 denote the same parts in the configuration in FIG. 17, and a description thereof will be omitted. In this receiver, for example, a method of deciding an array output yi by a decision unit 191 and selecting an output dixe2x80x2 from the decision unit 191 as a reference signal by a selection unit 192 to calculate an error signal ∈ixe2x80x2 is used. More specifically, when an LMS algorithm is applied, by the following equation:
Wj,i+1=Wj,i+2xcexcxj,i*∈ixe2x80x2 ∈ixe2x80x2=dixe2x80x2xe2x88x92yi xe2x80x83xe2x80x83(4)
the complex weight wj is calculated. In this manner, since a signal controlled to an optimum value, the adaptive array communication system can improve a bit error rate performance in an array output yi. In addition,an error signal ∈ixe2x80x2 can be calculated even in a period having no reference signal di, and the LMS algorithm can be operated at a high accuracy.
Therefore, for example, when an adaptive array communication system using the decision feedback loop shown in FIG. 17 is applied to a system using convolutional coding/viterbi decoding as shown in FIG. 18, as shown in FIG. 18, re-encoded data of viterbi decoder output is assumed as a reference signal dixe2x80x2. The data is fedback to the adaptive array, so that the error signal xcex5ixe2x80x2 can be calculated. As a result, bit error rate performance in a decoded output of a viterbi decoder can be further improved.
However, in the conventional receiver as shown in FIG. 15, since calculation represented by Equation (3) is repeated until the complex weight wj converges to an optimum value by the adaptive algorithm, the error signal xcex5i is required. In the example using the LMS algorithm described above, when the error signal xcex5i is to be calculated, the known reference signal di described in Equation (2) is required. For this reason, when the reference signal di is ended before the complex weight wj is converged to an optimum value, that is, when the sequence length of the reference signal di is not sufficient, a correct error signal cannot be calculated. There is a problem that the complex weight wj is not converged to the optimum value and a problem that the bit error rate performance is degraded.
This problem will be described in more detail below with reference to the drawings. FIG. 19 is a graph showing a change in complex weight with time. For example, in an LMS algorithm, when the complex weight wj is controlled to an optimum value wopt on the basis of an error signal xcex5i between the reference signal di and the array output yi, as shown in FIG. 19, the complex weight wj becomes sequentially close to the optimum value wopt by the LMS algorithm. For this reason, when the reference signal di exists for a sufficiently long time, for example, until time t shown in FIG. 19, the complex weight is almost equal to the optimum value wopt. For this reason, a preferable characteristic can be realized. However, when the reference signal di exists for a short time, for example, when the reference signal di is ended until time t0, the complex weight wj is largely different from the optimum value, the characteristic is degraded.
On the other hand, when the sufficiently long reference signal di is used, the LMS algorithm is converged, and an optimum complex weight wopt can be calculated. However, insertion of the long reference signal disadvantageously causes transmission efficiency to be degraded.
When the LMS algorithm is converged by the short reference signal di to calculate an optimum complex weight, the variation of the optimum complex weight wopt with time cannot be neglected. More specifically, when the complex weight wopt varies with time in one burst period, a stable demodulation characteristic is not obtained, the characteristic is degraded. This phenomenon is generated such that an interference station or a self station moves or the reception power of a desired wave or an interference wave varies due to fading.
This problem will be described below by using the drawings. FIG. 20 is a graph showing a change of the complex weight wj with time. For example, if the optimum complex weight wopt is a constant value in one burst period, the complex weight wj obtained by the LMS algorithm is sequentially controlled to the optimum value wopt as indicated by a curve A. However, when a mobile station and an inerference station move or when a reception power varies due to fading, and when the optimum value wopt varies in one burst period as indicated by a curve B, the complex weight wj obtained by the LMS algorithm varies as indicated by a curve C, for example. In this case, since the reference signal di ends at time t, the complex weight wj can be controlled until time t as shown in FIG. 20. More specifically, after time t, the complex weight wj cannot be controlled, and the complex weight wj cannot be made close to the optimum value wopt indicated by a curve B. For this reason, bit error rate performance is degraded.
Therefore, for example, when the adaptive array communication system shown in FIG. 15 is applied to a system using convolutional coding/viterbi decoding as shown in FIG. 16, the same problems as described above are posed.
In order to solve the problems, when the conventional receiver as shown in FIG. 17 is used, a decision result dixe2x80x2 of an array output yi may be erroneous. For example, when the decision result dixe2x80x2 is erroneous, an error signal xcex5ixe2x80x2 obtained from the erroneous decision result is also erroneous. For this reason, a correct error signal can be obtained. Therefore, in an updating equation using the LMS algorithm expressed by Equation (4), the complex weight wj cannot be correctly controlled, and the characteristic is disadvantageously degraded.
For example, when an adaptive array communication system using the decision feedback loop shown in FIG. 17 is applied to the system using the convolutional coding/viterbi decoding as shown in FIG. 18, as shown in FIG. 18, re-encoded data of a viterbi decoder output is handled as a reference signal dixe2x80x2 . The data is fed back to the adaptive array, so that the error signal xcex5ixe2x80x2 can be calculated. For this reason, the possibility of falling in a vicious circle where erroneous control is caused by an error of the decision result can be reduced, and the characteristic can be suppressed from being degraded. However, it is generally known that a process delay required for viterbi decoding is large. For this reason, in a method of controlling the complex weight wj on the basis of the re-encoded data dixe2x80x2 of the viterbi decoder output as shown in FIG. 18, as in the case in which the LMS algorithm is applied without applying the convolutional coding/viterbi decoding described above, when an optimum complex weight varies with time in one burst period, the characteristic is degraded.
As an adaptive algorithm which can be applied to an adaptive array communication system based on the MSE criteria except for the LMS algorithm described in the above background art, for example, an SMI (Sample Matrix Inverse) algorithm for solving a normal equation or an RLS (Recursive Least Squares) algorithm for recursively calculating an inverse matrix is known. However, the SMI algorithm has a problem that a circuit scale is considerably increased because an inverse matrix calculation is necessary. In addition, in the RLS algorithm, although no inverse matrix calculation is necessary, as in the LMS algorithm, an error signal must be calculated when a complex weight is controlled. In addition, since a complicated recursive equation is used, the RLS algorithm has a problem that the circuit scale is inevitably increased.
It is an object of the present invention to provide an adaptive array communication system and a receiver being capable of realizing calculation of an optimum complex weight independently of the sequence length of a reference signal and being capable of realizing a preferable demodulation characteristic even though a reception power varies due to the movement of a mobile station and an interference station or fading to cause a complex weight to vary with time.
The adaptive array communication system according to one aspect of this invention includes a transmitter (corresponding to a convolutional encoder 1 and a QPSK modulator 2 according to an embodiment (to be described later)) for modulating coded information data by a predetermined modulation method, and a receiver (corresponding to a demodulator 3) which performs known viterbi decoding to a received signal from the transmitter to select a most likely path. The receiver further includes adaptive control unit (corresponding to an adaptive control unit 31) which performs weight control on the basis of a known adaptive algorithm for each state of the viterbi decoding, multiplies received signals from a plurality of antennas by complex weights which are different from each other for the respective states to perform weighting processes depending on the received signals, and, thereafter, combines the weighted signals to perform such control that a desired wave component is maximized and an interference wave component is minimized; decoding unit (corresponding to a decoding unit 34) which adds a branch metric and a path metric calculated by a difference between a signal obtained after the weighting combining and a reference signal (corresponding to a replicate signal) serving as an ideal received signal to calculate a metric corresponding to a state transition; and error vector calculation unit (corresponding to an error vector calculation circuit 33) which calculates an error vector for calculating complex weights which are different from each other for the respective states on the basis of the signal obtained after the weighting combining and the reference signal, and the directivities of the plurality of antennas are adaptively controlled to perform a process of removing an interference wave except for a desired wave and a process of combining a plurality of desired waves.
According to the above-mentioned aspect, there is provided an adaptive control unit which performs weight control for supplying an optimum complex weight for each state to maximize a weighted/combined desired wave component and to minimize an interference wave component is arranged to perform adaptive array control for each state of viterbi decoding. Even though a complex weight varies with time in one burst period, the adaptive array communication system can easily track the complex weight.
In the adaptive array communication system according to the next aspect of this invention, the transmitter makes a coding rate in convolutional coding variable (corresponding to a convolutional coder 4).
According to the above-mentioned aspect, coding rate is increased to (nxe2x88x921)/n by using a punctured code to improve transmission efficiency. In addition, the coding rate is set to be 1/n to improve error correction capability.
In the adaptive array communication system according to the next aspect, as a modulation method in the transmitter, a BPSK (corresponding to a BPSK modulator 6) or a QPSK (corresponding to a QPSK modulator 2) is used.
According to the above-mentioned aspect, by using the QPSK demodulation method, a preferable characteristic is obtained even in a severe environment. In addition, by using the BPSK modulation method, mapping is simplified.
The adaptive array communication system according to the next aspect includes a transmitter which modulates coded information data by a predetermined modulation method, and a receiver (corresponding to a demodulator 8) which performs known viterbi decoding to a received signal from the transmitter to select a most likely path. The receiver further includes an adaptive control unit which performs weight control on the basis of a known adaptive algorithm for each state of the viterbi decoding, multiplies received signals from a plurality of antennas by a complex weight shared by all the states to perform weighting processes depending on the received signals, and, thereafter, combines the weighted signals to perform such control that a desired wave component is maximized and an interference wave component is minimized; a decoding unit which adds a branch metric and a path metric calculated by a difference between a signal obtained after the weighting combining and a reference signal (replicate signal) serving as an ideal received signal to calculate a metric corresponding to a transition to a desired state; and an error vector calculation unit which calculates an error vector for calculating a complex weight which is shared by all the states on the basis of the signal obtained after the weighting combining and the reference signal, and further includes maximum-likely state decision unit (corresponding to a maximum-likely state decision circuit 52) which decides a complex weight in a maximum-likely state at a specific symbol timing as a complex weight shared by all states at the next symbol timing for each receiver, and the directivities of the plurality of antennas are adaptively controlled to perform a removing process of an interference wave except for a desired wave or a combining process of a plurality of desired waves.
According to the above-mentioned aspect, a complex weight in a maximum-likely state at a specific symbol timing is updated as a complex weight which is shared by all states at the next symbol timing.
In the adaptive array communication system according to the next aspect, LMS algorithm or RLS algorithm is used as the predetermined adaptive algorithm.
According to the above-mentioned aspect, for example, when the LMS algorithm is used as an adaptive algorithm, a calculation amount can be reduced. On the other hand, when the RLS algorithm is applied, although a calculation amount which is larger than that in the LMS algorithm is necessary, a converging rate of a complex weight can be increased.
The receiver according to the next aspect includes a configuration which performs known viterbi decoding to a signal from a transmitter which modulates coded information data by a predetermined modulation method, an adaptive control unit which performs weight control on the basis of a known adaptive algorithm for each state of viterbi decoding, multiplies received signals from a plurality of antennas by complex weights which are different from each other for the respective states to perform weighting processes depending on the received signals, and, thereafter, combines the weighted signals to perform such control that a desired wave component is maximized and an interference wave component is minimized; a decoding unit which adds a branch metric and a path metric calculated by a difference between a signal obtained after the weighting combining and a reference signal (replicate signal) serving as an ideal received signal to calculate a metric corresponding to a transition to a desired state; and an error vector calculation unit which calculates an error vector for calculating complex weights which are different from each other for the respective states on the basis of the signal obtained after the weighting combining and the reference signal.
According to the above-mentioned aspect, an adaptive control unit which performs weight control for supplying an optimum complex weight for each state to maximize a weighted/combined desired wave component and to minimize an interference wave component is arranged to perform adaptive array control for each state of viterbi decoding. Even though a complex weight varies with time in one burst period, the receiver can easily follow the complex weight.
The receiver according to the next aspect includes a configuration which performs known viterbi decoding to a signal from a transmitter which modulates coded information data by a predetermined modulation method, an adaptive control unit which performs weight control on the basis of a known adaptive algorithm for each state of viterbi decoding, multiplies received signals from a plurality of antennas by a complex weight shared by all the states to perform weighting processes depending on the received signals, and, thereafter, combines the weighted signals to perform such control that a desired wave component is maximized and an interference wave component is minimized; a decoding unit which adds a branch metric and a path metric calculated by a difference between a signal obtained after the weighting combining and a reference signal (replicate signal) serving as an ideal received signal to calculate a metric corresponding to a transition to a desired state; and an error vector calculation unit which calculates an error vector for calculating a complex weight which is shared by all the states on the basis of the signal obtained after the weighting combining and the reference signal, and further includes a maximum-likely state decision unit which decides a complex weight in a maximum-likely state at a specific symbol timing as a complex weight shared by all states at the next symbol timing.
According to the above-mentioned aspect, a complex weight in a maximum-likely state at a specific symbol timing is updated as a complex weight which is shared by all states at the next symbol timing.
In the adaptive array communication system according to the next aspect, LMS algorithm or RLS algorithm is used as the predetermined adaptive algorithm.
According to the above-mentioned aspect, for example, when the LMS algorithm is used as an adaptive algorithm, a calculation amount can be reduced. On the other hand, when the RLS algorithm is applied, although a calculation amount which is larger than that in the LMS algorithm is necessary, a convergent rate of a complex weight can be increased.